Dataiku DSS MCP Server for Google ADK 14 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Dataiku DSS as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="dataiku_dss_agent",
instruction=(
"You help users interact with Dataiku DSS "
"using 14 available tools."
),
tools=[mcp_tools],
)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Dataiku DSS MCP Server
Connect your Dataiku DSS instance to any AI agent and take full control of your enterprise AI and collaborative data science workflows through natural conversation.
Google ADK natively supports Dataiku DSS as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 14 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
What you can do
- Project & Dataset Exploration — List all accessible DSS projects and retrieve structural extraction of dataset column schemas and types
- Pipeline Orchestration — Monitor build tasks and training runs by listing pipeline jobs and analyzing execution states and timing
- Transformation Auditing — Retrieve explicit configuration structures parsing precise Dataiku recipes (Python, SQL, Visual) to verify data logic
- Automation & Scenarios — List automation scenarios and trigger execution commands to rebuild pipelines or retrain models securely
- Model Monitoring — Identify saved ML models and retrieve detailed performance metrics defining specific trained schema layers
- Admin Oversight — Enumerate installed plugins and data connections (SQL, Cloud Storage, APIs) to verify organizational constraints
The Dataiku DSS MCP Server exposes 14 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Dataiku DSS to Google ADK via MCP
Follow these steps to integrate the Dataiku DSS MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 14 tools from Dataiku DSS via MCP
Why Use Google ADK with the Dataiku DSS MCP Server
Google ADK provides unique advantages when paired with Dataiku DSS through the Model Context Protocol.
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Dataiku DSS
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
Seamless integration with Google Cloud services means you can combine Dataiku DSS tools with BigQuery, Vertex AI, and Cloud Functions
Dataiku DSS + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Dataiku DSS MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Dataiku DSS and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Dataiku DSS tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Dataiku DSS regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Dataiku DSS
Dataiku DSS MCP Tools for Google ADK (14)
These 14 tools become available when you connect Dataiku DSS to Google ADK via MCP:
dataset_schema
Get the schema (columns, types) of a specific dataset
get_job
Get job state, timing, and outputs
get_model
Get saved model metadata, algorithm, and performance metrics
get_project
Get project metadata, settings, and tags
get_recipe
Get recipe configuration and settings
list_connections
List all DSS data connections (databases, cloud storage, APIs)
list_datasets
List all datasets in a project
list_jobs
List pipeline jobs in a project (build tasks, training runs)
list_models
List deployed/saved ML models in a project
list_plugins
List installed DSS plugins
list_projects
List all DSS projects accessible to the API key
list_recipes
List all recipes (data transformations) in a project
list_scenarios
List automation scenarios in a project
run_scenario
Trigger a scenario execution (build pipeline, retrain model)
Example Prompts for Dataiku DSS in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Dataiku DSS immediately.
"List all projects in my Dataiku instance"
"What is the schema for dataset 'raw_logs' in project 'FRAUD'?"
"Run scenario 'REBUILD_PIPELINE' in project 'SALES'"
Troubleshooting Dataiku DSS MCP Server with Google ADK
Common issues when connecting Dataiku DSS to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkDataiku DSS + Google ADK FAQ
Common questions about integrating Dataiku DSS MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
Connect Dataiku DSS with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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TypeScript toolkit for building AI-powered web applications.
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Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Dataiku DSS to Google ADK
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.